Optimization of web-based physics learning technology through on-demand microlearning video download facility in an internet accessibility variation case

Henry Praherdhiono, Yulias Prihatmoko


The research aims to see effectiveness through the perception of optimized physics learning web design through the development of on-demand microlearning video download facilities in diverse areas and access devices. Physics learning through web design, despite success in a variety of online learning methods, has major constraints on personalized learning. Individually, students have a variety of access devices and are in areas with a variable learning environment topology towards internet access. Agile development methods were developed to develop on-demand video download features on the physical learning web, and the development results were tested on MI-Ar Raudhah students based on characteristic compatibility. The development of the on-demand and simplified physical learning video download feature using microlearning is very effective for accessing students with varied Internet access devices and topologies.


Abdulrahaman, M. D., Faruk, N., Oloyede, A. A., Surajudeen-Bakinde, N. T., Olawoyin, L. A., Mejabi, O. V., Imam-Fulani, Y. O., Fahm, A. O., & Azeez, A. L. (2020). Multimedia tools in the teaching and learning processes: A systematic review. Heliyon, 6(11), e05312.
Admiraal, W. (2013). Meaningful learning from practice: Web-based video in professional preparation programmes in university. Technology, Pedagogy and Education, 23(4), 491–506. https://doi.org/10.1080/1475939x.2013.813403
Alonzo, A. C., & Kim, J. (2018). Affordances of video-based professional development for supporting physics teachers’ judgments about evidence of student thinking. Teaching and Teacher Education, 76, 283–297.
Azlan, C. A., Wong, J. H. D., Tan, L. K., A.D. Huri, M. S. N., Ung, N. M., Pallath, V., Tan, C. P. L., Yeong, C. H., & Ng, K. H. (2020). Teaching and learning of postgraduate medical physics using Internet-based e-learning during the COVID-19 pandemic – A case study from Malaysia. Physica Medica, 80, 10–16. https://doi.org/10.1016/j.ejmp.2020.10.002
B. Hobbs & Yvan Petit. (n.d.). Agile Methods on Large Projects in Large Organizations.
Bonus, J. A., & Watts, J. (2021). You can [’t] catch the sun in a net!: Children’s misinterpretations of educational science television. Journal of Experimental Child Psychology, 202, 105004.
Canfield, C. I., Egbue, O., Hale, J., & Long, S. (2019). Opportunities and challenges for rural broadband infrastructure investment.
Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J., & Zheng, J. (2020). The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research, 287, 112934. https://doi.org/10.1016/j.psychres.2020.112934
Herder, T., & Rau, M. A. (2022). Representational-competency supports in the context of an educational video game for undergraduate astronomy. Computers & Education, 190, 104602.
Hill, M. E., Aliaga, S. R., & Foglia, E. E. (2022). Learning with digital recording and video review of delivery room resuscitation. Seminars in Fetal and Neonatal Medicine, 27(5), 101396. https://doi.org/10.1016/j.siny.2022.101396
Lam, S., & Chan, M. (2021, December 5). Animated MOOC Videos on Semiconductor Devices and Their Versatile Use for Self-Learning & Formal Teaching Delivery. 2021 IEEE International Conference on Engineering, Technology & Education (TALE). https://doi.org/10.1109/tale52509.2021.9678865
Mulhayatiah, D., Sinaga, P., Rusdiana, D., Kaniawati, I., & Junissetiawati, D. (2022). Modern Physics E-book Based Multirepresentation for Hybrid Learning. European Online Journal of Natural and Social Sciences, 11(4), 1166–1177.
Neelakandan, S., Annamalai, R., Rayen, S. J., & Arunajsmine, J. (2020). Social media networks owing to disruptions for effective learning. Procedia Computer Science, 172, 145–151.
Odriozola-González, P., Planchuelo-Gómez, Á., Irurtia, M. J., & De Luis-García, R. (2020). Psychological effects of the COVID-19 outbreak and lockdown among students and workers of a Spanish university. Psychiatry Research, 290, 113108. https://doi.org/10.1016/j.psychres.2020.113108
Otero, T. F., Barwaldt, R., Topin, L. O., Vieira Menezes, S., Ramos Torres, M. J., & de Castro Freitas, A. L. (2020, October 21). Agile methodologies at an educational context: A systematic review. 2020 IEEE Frontiers in Education Conference (FIE). https://doi.org/10.1109/fie44824.2020.9273997
P. Abrahamsson, O. Salo, Jussi Ronkainen, & J. Warsta. (n.d.). Agile Software Development Methods: Review and Analysis.
Pereira, R., & Tam, C. (2021). Impact of enjoyment on the usage continuance intention of video-on-demand services. Information & Management, 58(7), 103501. https://doi.org/10.1016/j.im.2021.103501
Pimentel, M. da G. C., Yaguinuma, C. A., Martins, D. S., & Zaine, I. (2019, April 8). Anchoring interactive points of interest on web-based instructional video. Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing. https://doi.org/10.1145/3297280.3297521
Profitiliotis, G., & Theologou, K. (2023). The monstrosity of the search for extraterrestrial life: Preparing for a future discovery. Futures, 147, 103117.
Quesada-Pallarès, C. (2019). Online vs. Classroom Learning: Examining Motivational and Self-Regulated Learning Strategies Among Vocational Education and Training Students. Frontiers in Psychology, 10(13 cites: https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85077371061 & origin=inward). https://doi.org/10.3389/fpsyg.2019.02795
Saputra, M., & Kuswanto, H. (2019). The Effectiveness of Physics Mobile Learning (PML) with HomboBatu Theme to Improve the Ability of Diagram Representation and Critical Thinking of Senior High School Students. International Journal of Instruction, 12(2), 471–490.
Saurabh, S., & Gautam, S. (2019). Modelling and statistical analysis of YouTube’s educational videos: A channel Owner’s perspective. Computers & Education, 128, 145–158.
Suwadi, N. A., & Lam, M. C. (2020). Smartphone-based Face-to-Face Collaborative Augmented Reality Architecture for Assembly Training. Fusion 2020, 50.
Syefrinando, B., Sukarno, S., Ariawijaya, M., & Nasukha, A. (2022). The Effect of Digital Literacy Capabilities and Self-Regulation on the Student’s Creativity in Online Physics Teaching. Jurnal Pendidikan IPA Indonesia, 11(3), 489–499.
Wong, W. Y., & Reimann, P. (2009, July). Web Based Educational Video Teaching and Learning Platform with Collaborative Annotation. 2009 Ninth IEEE International Conference on Advanced Learning Technologies. https://doi.org/10.1109/icalt.2009.223
Yoon, M., Lee, J., & Jo, I.-H. (2021). Video learning analytics: Investigating behavioral patterns and learner clusters in video-based online learning. The Internet and Higher Education, 50, 100806.
Zendle, D., Kudenko, D., & Cairns, P. (2018). Behavioural realism and the activation of aggressive concepts in violent video games. Entertainment Computing, 24, 21–29.


Henry Praherdhiono
henry.praherdhiono.fip@um.ac.id (Primary Contact)
Yulias Prihatmoko
Praherdhiono, H., & Prihatmoko, Y. (2023). Optimization of web-based physics learning technology through on-demand microlearning video download facility in an internet accessibility variation case. Momentum: Physics Education Journal, 7(2), 290–298. https://doi.org/10.21067/mpej.v7i2.8527

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